Abstract. In this paper we present a model for the carpet cutting problem in which carpet shapes are cut from a rectangular carpet roll with a fixed width and sufficiently long le...
Andreas Schutt, Peter J. Stuckey, Andrew R. Verden
Automated feature discovery is a fundamental problem in machine learning. Although classical feature discovery methods do not guarantee optimal solutions in general, it has been r...
Empirical divergence maximization is an estimation method similar to empirical risk minimization whereby the Kullback-Leibler divergence is maximized over a class of functions tha...
In this paper, we present two near-optimal methods to determine the real-time collision-free path for a mobile vehicle moving in a dynamically changing environment. The proposed de...
Jian Yang, Zhihua Qu, Jing Wang 0005, Kevin L. Con...
Constraints and quantitative preferences, or costs, are very useful for modelling many real-life problems. However, in many settings, it is difficult to specify precise preference ...
Mirco Gelain, Maria Silvia Pini, Francesca Rossi, ...
The recent literature has provided a solid theoretical foundation for the use of schema mappings in data-exchange applications. Following this formalization, new algorithms have b...
Bruno Marnette, Giansalvatore Mecca, Paolo Papotti
Decentralized planning in uncertain environments is a complex task generally dealt with by using a decision-theoretic approach, mainly through the framework of Decentralized Parti...
The question of nonemptiness of the intersection of a nested sequence of closed sets is fundamental in a number of important optimization topics, including the existence of optima...
Abstract. In this paper, we empirically investigate the NP-hard problem of finding sparsest solutions to linear equation systems, i.e., solutions with as few nonzeros as possible. ...
This paper describes a novel solution to the rigid point pattern matching problem in Euclidean spaces of any dimension. Although we assume rigid motion, jitter is allowed. We pres...